> ## Documentation Index
> Fetch the complete documentation index at: https://docs.kalarislabs.com/llms.txt
> Use this file to discover all available pages before exploring further.

# torch-geometric — AI agent skill for data science and ml

> PyTorch Geometric (PyG) for graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neig…

# `torch-geometric`

> PyTorch Geometric (PyG) for graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets. Use when working with torch\_geometric, not for general NetworkX analytics or non-graph PyTorch models.

**Category:** [data-science-and-ml](/research-agent-skills/skills#data-science-and-ml) · **License:** MIT · **Version:** 1.2

## Install

```bash theme={null}
npx research-agent-skills install torch-geometric
npx skills add KalarisLabs/research-agent-skills --skill torch-geometric
```

## When to use it

PyTorch Geometric (PyG) for graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets. Use when working with torch\_geometric, not for general NetworkX analytics or non-graph PyTorch models.

## Full playbook

Read [SKILL.md](https://github.com/KalarisLabs/research-agent-skills/blob/main/skills/torch-geometric/SKILL.md) for the complete workflow, references and any scripts. The agent installer copies the full skill folder.


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